IBM deploys Nvidia HGX B300 cluster on IBM Cloud, targeting regulated AI workloads

IBM has made Nvidia’s HGX B300 GPU systems available on IBM Cloud, giving regulated industries access to some of the most powerful AI training hardware on the market through a managed cloud environment. The systems went live around April 29, marking the latest step in an expanded partnership between the two companies that was first announced at GTC 2026 in March. What’s inside the box Each HGX B300 system packs eight Blackwell Ultra GPUs into a single node. The raw compute numbers are staggering: up to 144 PFLOPS in FP4 precision and 72 PFLOPS in FP8. Each system offers more than 2 TB of shared HBM3e memory, which matters enormously for large language model training where the entire model needs to fit in GPU memory to avoid performance-killing data shuffling. The networking side runs at 800 Gb/s per GPU via Nvidia’s ConnectX-8 adapters, ensuring that multi-node training jobs don’t bottleneck at the interconnect layer. The compliance angle The HGX B300 deployment integrates with Red Hat OpenShift and IBM’s watsonx platform, creating what IBM frames as a complete stack for governed AI workflows. OpenShift handles the container orchestration that lets workloads move between on-premise...